Plotly

library(tidyverse)

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library(p8105.datasets)
library(plotly)

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We are going to look at “The Instacart Online Grocery Shopping Dataset 2017”, we are only interested in items ordered in produce, snack, and beverage department on weekdays.

data("instacart")

instacart = instacart |> 
  select(add_to_cart_order, reordered, order_number, department, aisle, days_since_prior_order, product_name, order_dow, order_hour_of_day) |>
  filter(department %in% c("produce", "snacks", "beverages")) |>
  filter(order_dow %in% c("1", "2", "3", "4", "5"))

The bar plot shows the number of items ordered in each aisle in produce, beverages, and snacks department.

instacart |> 
  group_by(department) |>
  count(aisle) |> 
  mutate(aisle = fct_reorder(aisle, n),
         text_label = "Department", department) |> 
  plot_ly(
    x = ~aisle, y = ~n, type = "bar", color = ~department, text = ~text_label, alpha = 0.5)

The scatter plot shows the tendency of reorder in different hours of the day.

instacart |>
  group_by(order_hour_of_day) |>
  mutate(reordered=mean(reordered))|>
  plot_ly(x = ~order_hour_of_day, y = ~reordered, type = "scatter", mode = "markers")

The box plot compares order in which each product was added to cart in different department.

instacart |>
  mutate(department = fct_reorder(department, add_to_cart_order)) |>
  plot_ly(y = ~add_to_cart_order, color = ~department, type = "box")